MesenCult™ Adipogenic Differentiation Kit (Mouse)

For the in vitro differentiation of mouse MSCs, ADSCs, and MEFs into adipocytes

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MesenCult™ Adipogenic Differentiation Kit (Mouse)

For the in vitro differentiation of mouse MSCs, ADSCs, and MEFs into adipocytes

1 Kit
Catalog #05507
234 USD

Required Products

Overview

MesenCult™ Adipogenic Differentiation Kit (Mouse) is specifically formulated for the in vitro differentiation of mouse mesenchymal stem and progenitor cells (MSCs), adipose tissue-derived MSCs (ADSCs), and mouse embryonic fibroblasts (MEFs) into cells of the adipogenic lineage.
NOTE: MesenCult™ Adipogenic Differentiation Medium must be supplemented with L-Glutamine (Catalog #07100).
Advantages:
• Compatible with mouse MSCs previously culture-expanded using the MesenCult™ Expansion Kit (Mouse).
• Available in an easy-to-use two-component format.
• Rigorous raw material screening and quality control minimize lot-to-lot variablity.
Components:
  • MesenCult™ MSC Basal Medium (Mouse), 200 mL
  • MesenCult™ Adipogenic Differentiation 10X Supplement (Mouse), 22 mL
Subtype:
Specialized Media
Cell Type:
Mesenchymal Stem and Progenitor Cells
Species:
Mouse
Application:
Differentiation
Brand:
MesenCult
Area of Interest:
Stem Cell Biology

Scientific Resources

Educational Materials

(3)

Product Applications

This product is designed for use in the following research area(s) as part of the highlighted workflow stage(s). Explore these workflows to learn more about the other products we offer to support each research area.

Data and Publications

Publications

(3)
Scientific reports 2019 nov

Machine Learning to Quantitate Neutrophil NETosis.

L. Elsherif et al.

Abstract

We introduce machine learning (ML) to perform classification and quantitation of images of nuclei from human blood neutrophils. Here we assessed the use of convolutional neural networks (CNNs) using free, open source software to accurately quantitate neutrophil NETosis, a recently discovered process involved in multiple human diseases. CNNs achieved {\textgreater}94{\%} in performance accuracy in differentiating NETotic from non-NETotic cells and vastly facilitated dose-response analysis and screening of the NETotic response in neutrophils from patients. Using only features learned from nuclear morphology, CNNs can distinguish between NETosis and necrosis and between distinct NETosis signaling pathways, making them a precise tool for NETosis detection. Furthermore, by using CNNs and tools to determine object dispersion, we uncovered differences in NETotic nuclei clustering between major NETosis pathways that is useful in understanding NETosis signaling events. Our study also shows that neutrophils from patients with sickle cell disease were unresponsive to one of two major NETosis pathways. Thus, we demonstrate the design, performance, and implementation of ML tools for rapid quantitative and qualitative cell analysis in basic science.
Journal of biomedical materials research. Part A 2019 jul

Aligned fibrous decellularized cell derived matrices for mesenchymal stem cell amplification.

M. Ventre et al.

Abstract

Biochemical and biophysical stimuli of stem cell niches finely regulate the self-renewal/differentiation equilibrium. Replicating this in vitro is technically challenging, making the control of stem cell functions difficult. Cell derived matrices capture certain aspect of niches that influence fate decisions. Here, aligned fibrous matrices synthesized by MC3T3 cells were produced and the role of matrix orientation and stiffness on the maintenance of stem cell characteristics and adipo- or osteo-genic differentiation of murine mesenchymal stem cells (mMSCs) was investigated. Decellularized matrices promoted mMSC proliferation. Fibrillar alignment and matrix stiffness work in concert in defining cell fate. Soft matrices preserve stemness, whereas stiff ones, in presence of biochemical supplements, promptly induce differentiation. Matrix alignment impacts the homogeneity of the cell population, that is, soft aligned matrices ameliorate the spontaneous adipogenic differentiation, whereas stiff aligned matrices reduce cross-differentiation. We infer that mechanical signaling is a dominant factor in mMSC fate decision and the matrix alignment contributes to produce a more homogeneous environment, which results in a uniform response of cells to biophysical environment. Matrix thus produced can be obtained in vitro in a facile and consistent manner and can be used for homogeneous stem cell amplification or for mechanotransduction-related studies.
Nature communications 2019

IL-33-mediated mast cell activation promotes gastric cancer through macrophage mobilization.

M. F. Eissmann et al.

Abstract

The contribution of mast cells in the microenvironment of solid malignancies remains controversial. Here we functionally assess the impact of tumor-adjacent, submucosal mast cell accumulation in murine and human intestinal-type gastric cancer. We find that genetic ablation or therapeutic inactivation of mast cells suppresses accumulation of tumor-associated macrophages, reduces tumor cell proliferation and angiogenesis, and diminishes tumor burden. Mast cells are activated by interleukin (IL)-33, an alarmin produced by the tumor epithelium in response to the inflammatory cytokine IL-11, which is required for the growth of gastric cancers in mice. Accordingly, ablation of the cognate IL-33 receptor St2 limits tumor growth, and reduces mast cell-dependent production and release of the macrophage-attracting factors Csf2, Ccl3, and Il6. Conversely, genetic or therapeutic macrophage depletion reduces tumor burden without affecting mast cell abundance. Therefore, tumor-derived IL-33 sustains a mast cell and macrophage-dependent signaling cascade that is amenable for the treatment of gastric cancer.
STEMCELL TECHNOLOGIES INC.’S QUALITY MANAGEMENT SYSTEM IS CERTIFIED TO ISO 13485. PRODUCTS ARE FOR RESEARCH USE ONLY AND NOT INTENDED FOR HUMAN OR ANIMAL DIAGNOSTIC OR THERAPEUTIC USES UNLESS OTHERWISE STATED.